id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1588516592,PR_kwDOAMm_X85KLKUD,7540,added 'storage_transformers' to valid_encodings,7460993,open,0,,,4,2023-02-16T23:29:44Z,2023-03-26T20:02:40Z,,FIRST_TIME_CONTRIBUTOR,,0,pydata/xarray/pulls/7540,"This PR adds ""storage_transformers"" to the valid encodings of a variable, thus allowing Zarr stores to be written using the 
new sharding storage transformers. 

Example of usage:

```python
import xarray as xr
import numpy as np
from zarr._storage.v3_storage_transformers import ShardingStorageTransformer
from zarr._storage.v3 import DirectoryStoreV3

# Dummy dataset
da = xr.DataArray(np.random.randn(1000, 1000), dims=(""x"", ""y""))
ds = xr.Dataset(dict(dummy_var=da))
ds = ds.chunk({""x"": 100, ""y"": 100})

# Sharded store and sharding transformer
store = DirectoryStoreV3(""/home/user/dummy-sharded-store.zarr"")
transformer = ShardingStorageTransformer(""indexed"", chunks_per_shard=(5, 1))

# Write sharded store
ds.to_zarr(
    store,
    encoding={""dummy_var"": {""storage_transformers"": [transformer]}},
    zarr_version=3,
)
```









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